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Working with Data in PyTorch

Master the Dataloader Class in PyTorch

The Gradient Team


In this tutorial, we'll deal with a fundamental challenge in Machine Learning and Deep Learning that is easier said than done: loading and handling different types of data. Specifically, we'll cover:

  • Looking at built-in datasets in-depth
  • Using the Dataloader class
  • Using GPUs vs. CPUs
  • Transforming and rescaling the data
  • Loading and visualizing built-in datasets
  • Building and loading custom datasets with PyTorch

For a more detailed breakdown of the code, check out the full tutorial on the blog.